The refugee crisis is perhaps the single most challenging problem for Europe today. Hundreds of thousands of people have already traveled across dangerous sea passages from Turkish shores to Greek islands, resulting in thousands of dead and missing, despite the best rescue efforts from both sides. One of the main reasons is the total lack of any early warning-alerting system, which could provide some preparation time for the prompt and effective deployment of resources at the hot zones. This work is such an attempt for a systemic analysis of the refugee influx in Greece, aiming at (a) the statistical and signal-level characterization of the smuggling networks and (b) the formulation and preliminary assessment of such models for predictive purposes, i.e., as the basis of such an early warning-alerting protocol. To our knowledge, this is the first-ever attempt to design such a system, since this refugee crisis itself and its geographical properties are unique (intense event handling, little or no warning). The analysis employs a wide range of statistical, signal-based and matrix factorization (decomposition) techniques, including linear & linear-cosine regression, spectral analysis, ARMA, SVD, Probabilistic PCA, ICA, K-SVD for Dictionary Learning, as well as fractal dimension analysis. It is established that the behavioral patterns of the smuggling networks closely match (as expected) the regular burst and pause periods of store-and-forward networks in digital communications. There are also major periodic trends in the range of 6.2-6.5 days and strong correlations in lags of four or more days, with distinct preference in the Sunday-Monday 48-hour time frame. These results show that such models can be used successfully for short-term forecasting of the influx intensity, producing an invaluable operational asset for planners, decision-makers and first-responders.

Results of the application of pattern recognition techniques to the problem of identifying Giant Radio Sources (GRS) from the data in the NVSS catalog are presented and issues affecting the process are explored. Decision-tree pattern recognition software was applied to training set source pairs developed from known NVSS large angular size radio galaxies. The full training set consisted of 51,195 source pairs, 48 of which were known GRS for which each lobe was primarily represented by a single catalog component. The source pairs had a maximum separation of 20 arc minutes and a minimum component area of 1.87 square arc minutes at the 1.4 mJy level. The importance of comparing resulting probability distributions of the training and application sets for cases of unknown class ratio is demonstrated. The probability of correctly ranking a randomly selected (GRS, non-GRS) pair from the best of the tested classifiers was determined to be 97.8 +/- 1.5%. The best classifiers were applied to the over 870,000 candidate pairs from the entire catalog. Images of higher ranked sources were visually screened and a table of over sixteen hundred candidates, including morphological annotation, is presented. These systems include doubles and triples, Wide-Angle Tail (WAT) and Narrow-Angle Tail (NAT), S- or Z-shaped systems, and core-jets and resolved cores. While some resolved lobe systems are recovered with this technique, generally it is expected that such systems would require a different approach.

Amid surging investment in artificial intelligence over the past few years and continuing concern about the implications of the technology, the White House announced on Tuesday that it intends to hold a series of workshops and form an interagency working group to examine the benefits and risks of AI. In a blog post, Ed Felten, Deputy US Chief Technology Officer, framed the issue in a way that excludes speculative scenarios presenting AI as a threat to humanity, a concern raised by the likes of Stephen Hawking and Elon Musk. While worries about runaway malevolent AI are often raised in public discussions of the technology, real AI research is more mundane, as in Google's effort to improve the conversational capabilities of its software by feeding it romance novels. "Today's AI is confined to narrow, specific tasks, and isn't anything like the general, adaptable intelligence that humans exhibit," said Felten. "Despite this, AI's influence on the world is growing. The rate of progress we have seen will have broad implications for fields ranging from healthcare to image- and voice-recognition."

San Francisco (AFP) - A US judge rejected a request by Facebook to toss out a civil suit accusing it of violating privacy with face-recognition software to help "tag" people in pictures. A lawsuit filed by three Illinois residents under the auspices of the state's Biometric Information Privacy Act can proceed, US District Court Judge James Donato said. "The court accepts as true plaintiffs' allegations that Facebook's face recognition technology involves a scan of face geometry that was done without plaintiffs' consent," he said in the ruling. It appeared that legislators in Illinois passed the act to address emerging biometric technology such as Facebook face-recognition software at issue in the case, according to the judge. Facebook had argued in a motion to dismiss that analyzing uploaded photographs did not qualify as biometric data and that the Illinois law did not apply.

SpaceX successfully launched a Falcon 9 rocket on Friday and, despite the odds, landed the first stage on a ship in the Atlantic Ocean. A SpaceX Dragon cargo spaceship was grappled by the International Space Station's Canadarm2 on April 10, following an April 8 launch from Cape Canaveral. CAPE CANAVERAL -- The coming week is another big one for SpaceX, whose unmanned Dragon capsule is scheduled to depart the International Space Station and return to Earth on Wednesday morning. The station's 58-foot robotic arm is expected to release the Dragon and its 3,700 pounds of cargo at 9:18 a.m. Because of a failed launch last summer, this Dragon will be the first to return science experiments and hardware from the ISS in a year.

A woman accused of "capitalizing on her physical attraction" to steal the identities of people she met on dating and home rental websites will face a judge Wednesday after she was arrested at a luxury hotel in Santa Barbara, according to the Los Angeles County Sheriff's Department. Maria Christina Johnson, 43, is believed to have dated or rented from her victims to gain access to their homes, where she'd scavenged through their belongings to obtain enough personal information to open new lines of credit without their knowledge, authorities said. Johnson -- also known as Maria Hendricks, Gia Hendricks, Maria Christina Gia and Maria Hainka -- has been arrested and charged multiple times before for various forms of fraud, identity theft and burglary before, according to a statement from the sheriff's department. After she successfully assumed an identity, investigators say, she moved into high-end hotels and charged thousands of dollars of goods and services to her victims, even attempting to purchase a car at one point, authorities said. By the time she was arrested as a guest of a luxury, beachside coastal resort in Santa Barbara on Thursday, investigators estimated Johnson, who lists her occupation as a dog trainer, had spent more than 250,000 of her victims' funds.

When it was revealed that Google's London-based company DeepMind would be able to access the NHS records of 1.6 million patients who use three London hospitals run by the Royal Free NHS trust – Barnet, Chase Farm and the Royal Free – it rang alarm bells. Not just because Google, a sprawling octopus of a company with tentacles in all our lives, wishes to "organise the world's information". Not just because patients are unlikely to have consented to Google having this information. The issue for many is the intertwining of these concerns with the idea of artificial intelligence (AI). DeepMind is no ordinary company.

One of the many industries that AI (Artificial Intelligence) can transform is healthcare. Since health is such an important thing, enhancements in healthcare industry can have a significant effect on human life. So far one of the major areas in which AI has been used in Healthcare is InsurTech and range of applications improving the complex and massive insurance industry. At this point healthcare industry is believed to be operating inefficiently on many counts. For example, in 2014, the US Government Accountability Office reported a 77.4 billion in improper payments of Medicare and Medicaid altogether.

Google has been granted access to approximately 1.6 million NHS patient records so that its artificial intelligence company can develop an app-based healthcare warning system. According to New Scientist magazine, the data sharing agreement gives Google's artificial intelligence company DeepMind access to patient data at the Royal Free, Barnet and Chase Farm hospitals run by the Royal Free NHS Trust. The deal, which makes five years' worth of data available, will be used by DeepMind to build an app-based early warning system for patients at risk of acute kidney injuries. However, Google has not ruled out using the information for other purposes if it involved improving healthcare. The shared data includes full names and patient histories, as well as sensitive information on HIV testing, details of abortions, drug overdoses and real-time NHS data on admissions, discharges and patient transfers.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display